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Granville Matheson
I am an academic data scientist with a background in neuroscience. Of the various types of data scientist, I am a generalist, but with a focus on statistics. My work has made international news and been cited in policy1, I have been involved in developing consensus guidelines for study reporting in my field to ensure replicable outcomes2 and software that I developed for pharmacokinetic modelling3 is currently in use in numerous institutions across the world for the analysis of complex data. I am passionate about learning new things, and enjoy the challenge of presenting complex results in a compelling way to audiences with different backgrounds.
I am currently looking for a position that allows me to work with and develop tools for understanding complex data to derive useful insights.
Education
PhD, Medical Science
Stockholm, Sweden
Karolinska Institutet
2018 - 2014
- Thesis: Reliability, Replicability and Reproducibility in PET Imaging
- Working with PET imaging of the dopamine system in psychosis and proneness to developing psychosis, as well as methods development.
MSc, Cognitive Neuroscience
Utrecht, The Netherlands
Universiteit Utrecht
2013 - 2010
- Cognitive Neuroscience Track
Selected Positions
Postdoctoral Researcher
Columbia University
Molecular Imaging / Biostatistics
2022 - 2020
- The plan is to work on developing Bayesian methods for performing pharmacokinetic modelling using a multilevel framework, using Markov Chain Monte Carlo.
- Preliminary results demonstrate large increases in accuracy and power.
Research Assistant
Karolinska Institutet
Cervenka Lab, PET Group
2014 - 2013
- Working on analysing the Karolinska Database to examine seasonal and diurnal effects of protein expression
Selected Writing
Pharmacokinetic Modelling of PET Data in R using kinfitr. Part 2: Basics and Iteration4
granvillematheson.com
N/A
2020
- Part 2 of a four part series describing my kinetic modelling R package. Here I cover basic usage of the package. I cover bias-variance tradeoffs and other relevant considerations during modelling.
My Physiological Response to my PhD Defence5
granvillematheson.com
N/A
2018
- I recorded my physiological data in the months leading up to my PhD defence, and analysed it here, using data visualisation to tell the story of my sleep changes, and heart rate, both before and during the defence.
- I also wrote an R package for extracting this data from the Withings API. I have been contacted by others from around the world who are using my software.